Geographic population health information system

ABSTRACT

A method and system for providing a data analysis in the form of a customized geographic visualization on a graphical user interface (GUI) on a remote client computing device using only a web browser on the remote client device. The system receives a user&#39;s selected data analysis to be performed by the system for display on the remote client device. The system verifies the data access permissions of the user to render a data analysis solution customized to that particular user, and automatically prevents that user from gaining access to data analysis solutions to which that user is prohibited. The system is configured to respond to the user&#39;s data analysis request, perform the necessary computations on the server side on the fly, and send a dataset interpretable by the client device&#39;s web browser for display on the client device or on a device associated with the client device.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No.62/247,190, filed Oct. 27, 2015, which is incorporated herein byreference in its entirety.

BACKGROUND

This application relates generally to the field of healthcare dataanalysis, and more specifically to systems and methods for displayinggeographic population health information.

Existing systems for analyzing population healthcare data based onpopulation distribution, disease state, and access to options to improvehealth requires software residing on the user's computing device orsystem to store, compute, manipulate, integrate multiple data sources,and display the results of massive datasets. Most likely, such softwareresiding on the user's computing device or system includes databasemanagement software to perform data management functions. As newdatasets are made available, software on the user's computing device orsystem requires updates to enable access to the new datasets as suchsoftware updates are released. In addition, to render a spatialdistribution on a user's computing device or system, existing methodsand systems require software on the user's computing device or system tofacilitate integration of the disparate data assets with geographicalinformation system software to produce a composite rendering on thegraphical user interface.

The proposed software and associated system of the instant disclosureaddresses these and other limitations of existing systems by using aclient device's web browser to display geographical population healthinformation data that the system collects, assembles, and preformatsfrom disparate data sources for on-demand, dynamic, interactive displayin the web browser.

SUMMARY

A geographic population health information system is disclosed,comprising: (a) a map server configured to receive client identificationinformation from a client device, the map server connected to a customgeographic data selection manager which is connected to a geo-spatialdatabase server, and (b) a web server configured to receive client userID information, the web server connected to a user security tabular dataassessor which is connected to a custom data selection manager, whereinthe custom data selection manager is connected to a plurality ofdatabases, wherein the geographic population information system isconfigured to asynchronously match the data from the geo-spatialdatabase server with data from the plurality of databases so as torender a user customized, dynamic visualization of healthcare data in aweb browser of the client device connected to the map server and the webserver.

A geographic population health information system is disclosedcomprising: (i) one or more first servers configured to: receive arequest from a client system for a geographical area and a desiredsegmenting of the geographical area; command a geo-spatial database todeliver one or more shapefiles based on the geographical area and thedesired segmenting of the geographical area, the one or more shapefilesincluding polygons with vertices having coordinates located within theouter boundaries; serve the shapefiles to the client system; (ii) theclient system, which is configured to: receive one or more sets ofhealth data after receiving the served shapefiles; match each portion ofthe received health data to at least one of the served shapefiles;generate shading instructions for at least some of the polygons of theone or more shapefiles based on the matched health data; produce aplurality of image tiles based on the served shapefiles and the shadinginstructions; arrange and display the plurality of image tiles on agraphical user interface of the client system.

The geographical area of the request may comprise coordinates of acenter of the geographical area and a zoom level.

The one or more servers may be configured to command the geo-spatialdatabase to deliver the one or more shapefiles based on the center ofthe geographical area and the zoom level.

The zoom level may correspond to a current zoom level of the graphicaluser interface of the client system.

The system may further comprise the one or more second servers, the oneor more second servers storing hypertension prevalence data for each ofa plurality of zip codes.

The client system may be configured to receive the hypertensionprevalence data as the one or more sets of health data and generate theshading instructions for the at least some of the polygons based on thereceived hypertension prevalence data.

The one or more second servers may be configured to serve at least someof the one or more sets of health data to the client system in a tabularformat.

The client system may be configured to display the at least some of theone or more sets of health data in the tabular format in response to auser selection.

The client system may be configured to map a user selection of a pixelof at least one of the one or more image tiles to the portion thereceived one or more sets of health data matched with a polygonencompassing the pixel.

The client system may be configured to display the matched portion ofthe received one or more sets of health data in tabular form in responseto the user selection of the pixel.

A geographic population health information system is disclosedcomprising: one or more first servers configured to: receive a requestfrom a client system for a layer including (a) one or more sets ofhealth data (b) a geographical area, and (c) a desired segmenting of thegeographical area; command a geo-spatial database to deliver one or moreshapefiles based on the geographical area and the desired segmenting ofthe geographical area, the one or more shapefiles including polygonswith vertices having coordinates located within the outer boundaries;receive the one or more sets of health data from one or more secondservers; match the each portion of the one or more sets of health datawith at least one of the polygons; generate shading instructions for atleast some of the polygons of the one or more shapefiles based on thereceived one or more sets of health data matched with the at least someof the polygons; produce a plurality of image tiles based on theshapefiles and the shading instructions; serve the plurality of imagetiles to the client system.

The geographical area of the request may comprise coordinates of acenter of the geographical area and a zoom level.

The one or more servers may be configured to command the geo-spatialdatabase to deliver the one or more shapefiles based on the center ofthe geographical area and the zoom level.

The zoom level may correspond to a current zoom level of a graphicaluser interface of the client system.

The system may further comprise the one or more second servers, the oneor more second servers storing hypertension prevalence data for each ofa plurality of zip codes.

The one or more first servers may be configured to receive thehypertension prevalence data as the one or more sets of health data andgenerate the shading instructions for the at least some of the polygonsbased on the received hypertension prevalence data.

The one or more first servers may be configured to serve at least someof the one or more sets of health data to the client system in a tabularformat.

The system may further comprise the client system, which is configuredto display the at least some of the one or more sets of health data inthe tabular format in response to a user selection.

The system may further comprise the client system, which is configuredto assemble and arrange the plurality of image tiles received from theone or more first servers in an array of image tiles.

The one or more first servers may be configured to serve tilearrangement instructions to the client system along with the pluralityof image tiles and the client system is configured to arrange theplurality of image tiles into the array based on the tile arrangementinstructions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates one embodiment of a system architecture of theinstant disclosure in block diagram form.

FIG. 2 illustrates a detailed block diagram of the client system shownin FIG. 1.

FIG. 3 illustrates a detailed block diagram of the customer geographicdata selection manager shown in FIG. 1.

FIG. 4 illustrates a detailed block diagram of the user security tabulardata assessor shown in FIG. 1.

FIGS. 5 to 52 illustrate various embodiments of geographic populationhealth information data displayed on a graphical user interfaceaccording to various constraints and filters.

DETAILED DESCRIPTION

Although the figures and the instant disclosure describe one or moreembodiments, one of ordinary skill in the art would appreciate that theteachings of the instant disclosure would not be limited to theseembodiments. Various embodiments of the instant disclosure relate tointegrating, analyzing, and visualizing geographic, population-based,health data on computer displays associated with one or more remoteclient computing devices without requiring client-side software on theclient device other than a web browser. The system herein disclosedeliminates the need for enterprise-wide software installations on clientdevices, and of the need to modify client-side computing devices toaccess the requested data. The system herein disclosed also avoids datacapacity limitations that would prevent the client computing device fromrendering the requested topographical data. The system provides userswith on-demand, user customized data analysis through a server systemthat may include a cloud-based server system.

Turning now to the drawings wherein like reference numerals refer tolike elements, FIG. 1 shows an illustration of one embodiment of asystem architecture that solves the problems associated with existingsystems. In this embodiment, system 10 includes server system 110hosting application software that responds to requests from clientsystem 100.

Server system 110 may include any web server such as a cloud-basedserver or a dedicated server system. Server system 110 in thisembodiment includes various hardware and software elements, includingmap server 111, custom geographic data selection manager 112, communityhealth management (CHM) web server 116, user security tabular dataassessor 117, and custom data selection manager 120. Referring to FIG.3, custom geographic data selection manager 112 may also include mapidentifier 113 and layer identifier 114. Referring to FIG. 4, usersecurity tabular data assessor 117 may include group security identifier118 and tabular layer identifier 119.

Server system 110 in this embodiment also includes connections tovarious databases, including geo-spatial database 115, claims database121, nutrition database 122, physical fitness database 123, and socialdeterminants of health database 124. One of ordinary skill wouldappreciate that in other embodiments, server system 110 may implementmultiple other servers and databases or fewer than what is shown inFIG. 1. Server system 110 may also include one or more computerprocessors, one or more data memory storage elements, one or moreinput/output buses and data ports to enable the communication of data toand from server system 110 via one or more wired, wireless, wifi,cellular, and satellite networks via the Internet, the world wide web,or any other communications protocol.

Geo-spatial database 115 may include and store a plurality ofshapefiles. Each shapefile may include one or more points or vertices,one or more lines connecting at least two vertices, and/or one or morepolygons connecting at least three vertices. Geo-spatial database 115may include and store at least one shapefile including a plurality ofpolygons, each corresponding to a respective zip code. Claims database121 may include geolocation data, organization data, and bar code scandata files. Nutrition database 122 may include healthcare administrativeclaims data. Physical fitness database 123 may include geological dataand image data of impervious surfaces. Social determinants of healthdatabase 124 may include alphanumeric descriptive data.

Client system 100 may include graphical user interface (GUI) 101, suchas a display, and Internet web browser 102, such as Internet Explorer,Safari, Firefox, or Google Chrome, to name a few. Client system 100 mayalso include client ID 108 representing a unique identifier that may beregistered with server system 110 so that server system 110 recognizesand returns requested data back to the same client device. Referring toFIG. 2, web browser 102 of client system 100 may include dynamic display103 including graphical image viewer 104, and web page renderer 105including image converter 106 and graphical composite assembler 107.

In one embodiment, map server 111 authenticates client ID 108 afterreceiving a service token from web browser 102. The custom geographicdata selection manager 112 receives the client input/selection (i.e.query) for a layer and retrieves, via layer identifier 114, one or moreshapefiles (or portions thereof) from geo-spatial database 115. The oneor more shapefiles (or portions thereof) retrieved from the geo-spatialdatabase 115 may be referred to as the appropriate shapefiles. Toretrieve the appropriate shapefiles, map identifier 113 of customgeographic data selection manager 112 uses a map identification routineto select the requested map, and layer identifier 114 of geographic dataselection manager 112 selects the appropriate layers from the selectedmap. The layers from the selected map include vertices files that arecombined to form the shapefile. The selected shapefile is sent to themap server 111 as a response to the original request from the webbrowser 102.

The custom data selection manager 112 may further retrieve, via mapidentifier 113, one or more reference shapefiles from an externaldatabase. The one or more reference shapefiles may be used to build anunderlying reference map upon which the appropriate shapefiles areoverlaid.

To retrieve the appropriate shapefiles and/or the reference shapefiles,layer identifier 114 and/or map identifier 113 of custom geographic dataselection manager 112 may determine outer coordinates of a displayedportion of the reference map. For example, the displayed portion of thereference map in FIG. 7 is almost the entire United States and smallportions of the Pacific and Atlantic Oceans, whereas the displayedportion of the reference map in FIG. 8 is Chicago. According to oneembodiment, map identifier 113 retrieves the reference shapefiles fromthe external server before the layer identifier 114 retrieves theappropriate shapefiles from the geo-spatial database 115.

To determine the outer coordinates layer identifier 114 may determine(a) a zoom level of a reference map currently displayed on GUI 101 and(b) a center of the reference map currently displayed on GUI 101. Layeridentifier 114 may learn the zoom level of the reference map by queryingthe client system 100. Alternatively, layer identifier 114 may havepreviously learned the zoom level of the reference map in order toretrieve appropriate reference shapefiles of the reference map. Based onthe zoom level and the center of the reference map, layer identifier 114may determine outer coordinates of a displayed portion of the referencemap. Alternatively or in addition, layer identifier 114 may determinethe outer coordinates of the displayed portion of the reference map bydetermining outer-most vertices, lines, or polygons of referenceshapefiles being used to render the displayed portion of the referencemap.

Layer identifier 114 may determine which sets of shapefiles stored inthe geo-spatial database 115 include the appropriate shapefiles based ona user selection of one or more layers on a drop-down menu displayed onGUI 101. For example, the geo-spatial database 115 may include (a) oneset of one or more shapefiles representing zip codes of the UnitedStates, (b) one set of one or more shapefiles representing state linesof the United States, (c) one set of one or more shape filesrepresenting city boundaries of the United States. Layer identifier 114may only retrieve shapefiles from the applicable sets of shapefiles. Forexample, if the user-selected layer is segmented according to zip code,but not according to city boundaries, then the layer identifier 114 mayonly retrieve shapefiles from sets (a) and/or (b), but not from set (c).

It should thus be appreciated that layer identifier 114 may determinethe applicable sets of shapefiles of geo-spatial database 115 and thatlayer identifier 114 may further determine the appropriate portions ofthe applicable sets. Put differently, layer identifier 114 may retrievethe appropriate shapefiles from the one or more applicable sets ofshapefiles. The appropriate shapefiles may include polygons having oneor more vertices with coordinates falling within the displayed portionof the reference map, lines having one or more vertices with coordinatesfalling within the displayed portion of the reference map, and/orvertices with coordinates falling within the displayed portion of thereference map. The appropriate shapefiles may be sent to the map server111 as a response to the original request from the web browser 102.

According to one embodiment, the map server 111 may serve theappropriate shapefiles (retrieved by the layer identifier 114) and/orthe reference shapefiles (retrieved by the map identifier 113) to theclient system 100. The graphical composite assembler 107 may receive theshapefiles from the map server 111 while waiting to receive thecustomized data from the CHM web server 116. Upon receiving thecustomized data, the graphical composite assembler 107 may match theappropriate shapefiles (but not the reference shapefiles) with thetabular data received from the CHM web server 116. The image converter106 may render a series of image tiles or raster files having thepolygons, lines, and/or vertices included in the reference shapefilesand the appropriate shapefiles. The polygons, lines, and/or vertices ofthe appropriate shapefiles may be overlaid on the polygons, lines,and/or vertices of the reference shapefiles and be shaded according tothe tabular data received from the CHM web server 116. The graphicalimage viewer 104 may assemble the rendered image tiles or raster filesinto an array according to assembly instructions produced by the imageconverter 106. The reference shapefiles may be rendered according toinstructions received from the external server.

According to another embodiment, the map server 111 may convert theappropriate shapefiles and the reference shapefiles into raster files orimage tiles. Each raster file or image tile may include polygons fromthe appropriate shapefiles, shaded according to the health data receivedfrom the CHM web server 116 and polygons from the reference shapefiles,shaded according to instructions received from the external server. Toperform the conversion, the map server 111 may fill in or shade eachpolygon included in the appropriate shapefiles based on tabular datareceived from the CHM web server 116. Put differently, the shading ofeach polygon of the appropriate shapefiles may be based on dataretrieved from CHM Web Server 116. As in the above embodiment, theshaded polygons of the appropriate shapefiles are overlaid on thepolygons of the reference shapefiles during rendering. The map server111 may deliver the raster files or image tiles (which may be images ofthe shaded polygons of the appropriate shapefiles overlaid onto thepolygons of the reference shapefiles), instead of the appropriateshapefiles and the reference shapefiles, to the client system 100. Thesize of each polygon may based, at least in part, on a zoom level of theGUI 101.

In one embodiment, graphical image viewer 104 is configured to displaygraphical images in various graphical file formats. Dynamic display 103of graphical image viewer 104 responds to inputs, such as macros, todynamically change the display of responsive data on the web browser 102in accordance with a user's commands. The dynamic display 103, forexample, is configured to enable a user to move or pan the imagedisplayed in web browser 102 and to zoom the image in or out. As theuser moves, pans, and/or zooms, the dynamic display 103 may update orcause map identifier 113 to update the reference shapefiles being usedto render the underlying reference map. As explained above, as thereference shapefiles used to display the underlying reference map areupdated, the appropriate shapefiles may also be updated. As the usermoves, pans, and/or zooms, the dynamic display 103 may update or causemap server 111 to serve (a) new shapefiles and/or (b) new raster filesor image tiles. Web page renderer 105, or similar rendering engine, ofweb browser 102 ensures the image is properly displayed on the web pagein the web browser 102. The web page renderer 105 combines variousformats, including HTML and CSS. In one embodiment, the image is in HTMLformat and the navigation on the web page is performed via CSS.

The graphical composite assembler 107 may receive the data in anasynchronous manner. According to one embodiment, the graphicalcomposite assembler 107 receives the appropriate shapefiles from the mapserver 111 and then instructs the image converter 106 to render theappropriate shapefiles according to health data later received from theCHM web server 116. According to another embodiment, the graphicalcomposite assembler 107 receives the raster files or image tiles frommap server 111 while waiting to receive customized data in tabularformat from the CHM web server 116. Upon receiving the customized datain tabular format, the graphical composite assembler 107 may match theraster files or image tiles with the appropriate tabular data into agraphical composite. Image converter 106 may convert the assembledgraphical composite into an image that can be viewed by the graphicalimage viewer 104.

Server system 110 is configured to receive entry by a user of serversystem 110 of a user ID 109 or other login credentials for ensuring thatthe user is provided access to only that information to which that useris allowed. Upon logging into the software hosted by server system 110,based upon the client identification and the login credentials of theuser, server system 110 automatically modifies the menu of selectableoptions displayed on graphical user interface 101 of client system 100for selection by the user. The user may then select from among one ormore data analysis from the menu that are pre-customized for that user.

In operation, a user using a client device, such as a desktop computer,a laptop, a tablet, or a mobile device, connected to server system 110would be provided by server system 110 with a login screen through whichthe user would enter the user's login credentials, such as login ID andpassword. Any variation of user authentication may be implemented byserver system 110 as may be known in the art. Server system 110 isconfigured to provide a menu of data analyses from which the user mayselect. Such data analyses may include the preparation by server system110 of a composite two-dimensional topographic map for display on thedisplay of the user's device. Server system 110 may provide the userwith various options or combination of elements from which the user mayselect that are associated with the requested data analysis.

Upon receipt of the user's request using web browser 102 connected toserver system 110, in one embodiment, cloud-based map server 111 ofserver system 110 separately sends a request to CHM Web server 116. Mapserver 111 verifies the client ID 108 of the user's client computingdevice and sends the request to custom geographic data selection manager112. Upon receipt of the request, geographic data selection manager 112uses the map identifier 113 and/or the layer identifier 114 to selectthe appropriate shapefiles from the geo-spatial database 115 to render amap. Geographic data selection manager 112 sends the appropriateshapefiles to the map server 111. According to one embodiment, and aspreviously stated, the map server 111 serves the appropriate shapefilesto the client system 100. According to another embodiment, and aspreviously stated, the map server 111 serves the raster files or imagetiles to web browser 102 of client system 100 for integration by webbrowser 102 into a map comprising a composite visualization of therequested data analysis.

Simultaneously, the CHM Web server 116 sends the request to the usersecurity data assessor 117 to verify the user's group ID 109 and thedata layer requested by the user. Upon verification that the userpermissions are satisfied, the user request is received by the customdata selection manager 120. The custom data selection manager 120queries the various databases 121,122,123,124 to retrieve the disparatedata. Upon receipt of the disparate data components from the custom dataselection manager 120, the CHM Web server 116 serves the data componentsto web browser 102 of client system 100 for integration by web browser102 into a map comprising a composite visualization of the requesteddata analysis. In this way, server system 110 conducts the spatial andstatistical analysis to match the user's request, and presents that datain a format that web browser 102 can interpret and assemble tographically display the results.

Web browser 102 uses graphical composite assembler 107 to match thetabular data with (a) the shapefiles or (b) the raster files/image tilesto produce a composite graphic. The graphical composite assembler 107may change the format of incoming data from the map server, which may bein the form of raster files, image files, and/or KML files. Imageconverter 106 converts the composite graphic into a Web page that can beviewed by graphical image viewer 104. Graphical image viewer 104displays the Web page through graphical user interface 101, which may beany one of a number of displays associated with client system 100. Webbrowser 102 stores the layer information to prevent the need for serversystem 110 to retrieve the same layer if the user selects the same layerwith new topographical elements.

Example: User Selection of Customized Data Analysis

In one example, a user wishes to conduct data analysis of a nationalaccount with employees across the 43,000 zip codes in the United States.In particular, the user desires to prioritize geographic areas where theaccount's employees have higher prevalence of hypertension in comparisonto the prevalence of the general commercial population. Furthermore, theuser seeks to limit the data analysis by controlling for socialdeterminants of health. Finally, the user needs to identify localproviders, community health centers, farmers markets, and socialservices that may be ideal partners to support population healthmanagement.

The user may log into the software hosted by server system 110 using aweb browser 102 displayed on the client device of client system 100. Theserver system 110 presents a customized menu 130 on the web pagedisplayed in the web browser 102 that is appropriate and/or customizedfor the user's user ID. The user may select the account and thehypertension prevalence layer. In addition, the user may select thelayer that controls for the social determinants of health. Lastly, theuser may select the local resources of interest.

The server system 110 automatically responds on the fly to the user'srequest by facilitating the collection and integration of data stored ondisparate data sources, and preformats the results in a way that isinterpretable and displayable by the user's web browser without anyadditional client-side software. The server system 110 pushes thatformatted data to the user's web browser, which renders theaccount-specific information for hypertension prevalence in a compositevisualization that allows the user to scan the map of the United States.The visualization renders an image of shape files for each zip codesymbolized and/or represented in different colors that reflect zip codeswith higher prevalence among the account population. Because the usercontrolled for social determinants of health, the visualization shadesthe shape files for the geographic areas controlled for by the user. Theuser may select or “click” on an area of the map and the shape fileproduces a pop-up display of the comparative data of the employeepopulation to the general commercial population. The file size for theimage could exceed 125 MB. By selecting providers and resources, theuser can click on the displayed community assets to reveal the servicesprovided by the local entity or hours of operation. Upon reviewing theservices, the user can receive directions to the local entity byentering an address associated with the user's geographic location.

FIGS. 5-52 provide the results displayed in graphical user interface(GUI) 101 of Internet browser 102 of various exemplary searches onserver system 110 that integrates community mapping data and socialdeterminants of health data overlaid on a graphical map of the UnitedStates. In these embodiments, the data is configured for display by zipcode. In other embodiments, the data may be displayed according to anyother actual, artificial, or synthetic geographic or other boundary orgrouping. For example, the data may be displayed by community, bycity/town, by township, by county, by state, and by region, or anycombination or subcombination of the foregoing.

Community mapping data may include data concerning medical conditionprevalence, medical condition frontier, food access frontier, nutrition,population density centers, and health care providers, as shown by thereferences positioned on the bottom ribbon on FIG. 7 after selecting thetab 126 of graphical user interface (GUI) 101 of Internet browser 102.

Social determinants of health data may include data concerning minoritypopulation prevalence, race/ethnicity prevalence, linguistic isolationprevalence, prevalence of a foreign language as the primary language,level of education, per capita income, income distribution, unemploymentprevalence, prevalence of population not in the labor force, povertyprevalence, prevalence of disabled people living in poverty, maritalstatus, prevalence of female only householders, prevalence of no accessto a vehicle, prevalence of the population enrolled in SupplementalNutritional Assistance Program (SNAP), and family size, as shown by thereferences positioned on the bottom ribbon on FIG. 20 after selectingtab 127 of graphical user interface (GUI) 101 of Internet browser 102.One of ordinary skill would appreciate that other community mapping dataand/or social determinants of health data may be utilized.

Condition prevalence in this disclosure refers to the proportion of thecommercial population that presents in a reporting period, for example,the preceding 12-month period, with one inpatient claim of a particularhealth condition of interest or 2 outpatient claims of the condition ofinterest in the reporting period. For example, a user seeking to knowthe proportion of the commercial population that presents in a reportingperiod, for example, the preceding 12-month period, with one inpatientclaim of a particular health condition of interest or 2 outpatientclaims of the condition of interest in the reporting period may querysystem 110, as shown in FIGS. 8-9.

In this embodiment, as shown in FIG. 8, after entering a location, suchas the name of a city, an address, or a zip code, into search box 128, auser may select the “hypertension prevalence” dropdown option 132 fromamong one or more selectable medical conditions in customized menu 130to obtain the percentage of the population in the geographic locationwho is considered to have hypertension. The prevalence of this conditionis presented to the user in graphical map image 134 where a differentcolor or shading style is assigned to each zip code shown in the image134 according to the prevalence of the item being searched. Thegeographic breadth of the image 134 may default to a particular zoomlevel, which zoom level may be adjustable by the user.

The image 134 is dynamically interactive with the user. Consequently,the user may select a particular color coded region corresponding to aparticular zip code to obtain further statistics on the prevalence ofthe condition being searched. As shown in FIG. 9, for example, the userselected the geographic tile 135 corresponding to zip code “36108” (item137), after which system 110 responds by displaying text box 136 withdetailed statistical data corresponding to that zip code and for theselected health condition, which in this example, is hypertensionprevalence, including community characteristics for the generalpopulation in that zip code. Legend 138 may be configured to dynamicallyupdate with information corresponding to the zoom level of image 134.

Condition frontier in this disclosure refers to, for any given medicalcondition selected above, the observed-to-expected ratio of thecommercial population compared to the general population. Populations inunderperforming zip codes may be identified relative to nationwide zipcodes with these characteristics. Social Determinants of Health (SDOH)include cultural factors (e.g., race/ethnicity and language), economicfactors (e.g., per capita income), educational factors (e.g., completionof primary education) and social factors (e.g., female head of householdand access to vehicle).

FIGS. 10 and 11 take the foregoing example a step further by identifyingone or more social factors that may explain the prevalence ofhypertension in the selected location. For example, once hypertensionprevalence displayed in the user's browser, the user may select“Hypertension Frontier” in the dropdown option 142 from among one ormore selectable options in customized menu 130 to identifyunderperforming zip codes relative to nationwide zip codes with similarcommunity characteristics. The prevalence of hypertension (or anycondition that is previously selected) is presented to the user ingraphical map image 144 where a different color or shading style isassigned to each zip code shown in the image 144 according to theprevalence of the item being searched. The geographic breadth of theimage 144 may default to a particular zoom level, which zoom level maybe adjustable by the user.

The image 144 is dynamically interactive with the user. Consequently,the user may select a particular color coded region corresponding to aparticular zip code to obtain further statistics on the item beingsearched (in this example, the hypertension frontier). As shown in FIG.11, for example, the user selected the geographic tile 145 correspondingto zip code “36117” (item 147), after which system 110 responds bydisplaying text box 146 with detailed statistical data corresponding tothat zip code and for the selected health condition, which in thisexample, is hypertension prevalence and the hypertensionobserved-to-expected ratio (O/E) associated with that condition for thatzip code, including community characteristics for the general populationin that zip code. Legend 148 may be configured to dynamically updatewith information corresponding to the zoom level of image 144.

Food access frontier in this disclosure refers to the availability offood options and access thereof, by zip code. The food access frontiercomparison considers relatively low areas of healthy food options (e.g.,“food deserts”) and high areas of unhealthy food options (e.g., “foodswamps”). The methodology employed by server system 110 may control formedian household income and commuting patterns, which may be describedas part of the economic sphere of daily activity. The calculated resultsmay be arrayed by deciles, as shown in FIGS. 12-13.

For example, after entering a location, such as the name of a city, anaddress, or a zip code, into search box 128, a user may select the “foodaccess frontier” dropdown option 152 from among one or more selectablenutritional options in customized menu 130 to obtain the availability bythe population to different food options in that geographic location.

As discussed above, the results of the food access frontier search forthe particular geographic location entered into search box 128 arepresented to the user in graphical map image 154 where a different coloror shading style is assigned to each zip code shown in the image 154according to the prevalence of the item being searched. The geographicbreadth of the image 154 may default to a particular zoom level, whichzoom level may be adjustable by the user.

As discussed above, the image 154 is dynamically interactive with theuser. Consequently, the user may select a particular color coded regioncorresponding to a particular zip code to obtain further statistics onthe food access frontier. As shown in FIG. 13, for example, the userselected the geographic tile 155 corresponding to zip code “36117” (item157), after which system 110 responds by displaying text box 156 withdetailed statistical data corresponding to that zip code and for theselected nutritional dropdown item. In this example, the food accessfrontier (in deciles), average distance to the nearest grocer, foodoptions within the daily commuting sphere, number of food options, andmedian household income may provide an indication of the environmentaland socioeconomic impact on health of the population represented by theselected geographic location. Legend 158 may be configured todynamically update with information corresponding to the zoom level ofimage 154.

Nutrition in this disclosure refers to a nutritional performancemeasure, which may compare scanned grocery store purchases at the zipcode level for both chain and independent stores. The comparison mayconsider fruits, whole grains, and vegetables relative to totalpurchases. The methodology employed by server system 110 may control formedian household income and commuting patterns, which may be describedas part of the economic sphere of daily activity. The calculated resultsmay be arrayed by deciles, as shown in FIGS. 14-15.

For example, after entering a location, such as the name of a city, anaddress, or a zip code, into search box 128, a user may select the“nutrition (decile)” dropdown option 162 from among one or moreselectable nutritional options in customized menu 130 to obtain foodpurchasing patterns at the selection location.

As discussed above, the results of the nutrition search for theparticular geographic location entered into search box 128 are presentedto the user in graphical map image 164 where a different color orshading style is assigned to each zip code shown in the image 164according to the prevalence of the item being searched. The geographicbreadth of the image 164 may default to a particular zoom level, whichzoom level may be adjustable by the user.

As discussed above, the image 164 is dynamically interactive with theuser. Consequently, the user may select a particular color coded regioncorresponding to a particular zip code to obtain further statistics onnutrition for the selected geographic location. As shown in FIG. 15, forexample, the user selected the geographic tile 165 corresponding to zipcode “02134” (item 167), after which system 110 responds by displayingtext box 166 with detailed statistical data corresponding to that zipcode and for the selected nutritional dropdown item. In this example,the nutritional performance (in deciles) and the observed-to-expected(O/E) ratio are presented in text box 166, which may provide anindication of the environmental and socioeconomic impact on health ofthe population represented by the selected geographic location. Legend168 may be configured to dynamically update with informationcorresponding to the zoom level of image 164.

Population density center in this disclosure refers to a measure of acommunity characteristic to provide the spatial location of thepopulation density. This measure may aggregates the location of thepopulation from the block level to the zip code. The measure calculationmay utilize US Census data at the block level to determine populationper square mile, as shown in FIGS. 16-17.

For example, after entering a location, such as the name of a city, anaddress, or a zip code, into search box 128, a user may select the“population density center” dropdown option 172 from among one or moreselectable community characteristics options in customized menu 130 toobtain the density of the population, among other statistics, at aselected location.

As discussed above, the results of the population density search for theparticular geographic location entered into search box 128 are presentedto the user in graphical map image 174 where a selectable iconcorresponding to population density and other statistics for thatgeographical location overlays image 174. The geographic breadth of theimage 174 may default to a particular zoom level, which zoom level maybe adjustable by the user.

As discussed above, the image 174 is dynamically interactive with theuser. Consequently, the user may select a particular icon to obtainfurther statistics on the geographic location. As shown in FIG. 17, forexample, the user selected the icon 175 corresponding to zip code“19143” (item 177), after which system 110 responds by displaying textbox 176 with detailed statistical data corresponding to people residingin that zip code and for the selected community characteristics dropdownitem.

Providers in this disclosure refers to the spatial location of healthcare providers in the community. In combination with other layers, thehealth care provider location layer allows users to identify potentialpartners to address population health.

As shown in FIGS. 18-19, after entering a location, such as the name ofa city, an address, or a zip code, into search box 128, one or morehealth care providers 182 may be displayed in image 184 that correspondto the selected location. For example, a user may select the “hospitals”or the “hospitals” and the “pharmacies” dropdown option 182 from amongone or more selectable provider options in customized menu 130 to obtaininformation concerning health care providers and/or pharmacies thatserve that particular location or geographic region.

As discussed above, the results of the provider search for theparticular geographic location entered into search box 128 are presentedto the user in graphical map image 184 where a selectable iconcorresponding to the selected item being searched and other statisticsfor that item are overlaid onto image 184. The geographic breadth of theimage 184 may default to a particular zoom level, which zoom level maybe adjustable by the user.

As discussed above, the image 184 is dynamically interactive with theuser. Consequently, the user may select a particular icon to obtainfurther statistics on the geographic location. As shown in FIGS. 18 and19, for example, the user selected the icon 185 corresponding to “NovantHealth Franklin Medical Center” (item 187 in FIG. 18) and “Walgreens”(item 187 in FIG. 19), after which system 110 responds by displayingtext box 186 with detailed statistical data corresponding to theselected health care provider.

Turning now to FIGS. 20-52, there is shown various exemplary searchoptions for various exemplary social determinants of health, suchminority population prevalence, race/ethnicity prevalence, linguisticisolation prevalence, prevalence of a foreign language as the primarylanguage, level of education, per capita income, income distribution,unemployment prevalence, prevalence of population not in the laborforce, poverty prevalence, prevalence of disabled people living inpoverty, marital status, prevalence of female only householders,prevalence of no access to a vehicle, prevalence of the populationenrolled in Supplemental Nutritional Assistance Program (SNAP), andfamily size, among others.

For example, FIGS. 21-22 show that after entering a location, such asthe name of a city, an address, or a zip code, into search box 128, auser may select the “minority (non-white)” dropdown option 192 fromamong one or more cultural factors options in customized menu 130 toobtain minority statistics of the population, among other statistics, atthe selected location.

As discussed above, the results of the minority search for theparticular geographic location entered into search box 128 are presentedto the user in graphical map image 194 where a different color orshading style is assigned to each zip code shown in the image 194according to the prevalence of the item being searched. The geographicbreadth of the image 194 may default to a particular zoom level, whichzoom level may be adjustable by the user.

As discussed above, the image 194 is dynamically interactive with theuser. Consequently, the user may select a particular color coded regioncorresponding to a particular zip code to obtain further statistics onnutrition for the selected geographic location. As shown in FIG. 22, forexample, the user selected the geographic tile 195 corresponding to zipcode “60085” (item 197), after which system 110 responds by displayingtext box 196 with detailed statistical data corresponding to that zipcode and for the selected cultural factors dropdown item. Legend 198 maybe configured to dynamically update with information corresponding tothe zoom level of image 194.

Similarly, FIGS. 23-24 show that after entering a location, such as thename of a city, an address, or a zip code, into search box 128, a usermay select the “Black (Race/Ethnicity)” dropdown option 202 from amongone or more cultural factors options in customized menu 130 to obtainminority statistics of the population, among other statistics, at theselected location.

As discussed above, the results of the black (race/ethnicity) search forthe particular geographic location entered into search box 128 arepresented to the user in graphical map image 204 where a different coloror shading style is assigned to each zip code shown in the image 204according to the prevalence of the item being searched. The geographicbreadth of the image 204 may default to a particular zoom level, whichzoom level may be adjustable by the user.

As discussed above, the image 204 is dynamically interactive with theuser. Consequently, the user may select a particular color coded regioncorresponding to a particular zip code to obtain further statistics onrace/ethnicity for the selected geographic location. As shown in FIG.24, for example, the user selected the geographic tile 205 correspondingto zip code “60636” (item 207), after which system 110 responds bydisplaying text box 206 with detailed statistical data corresponding tothat zip code and for the selected cultural factors dropdown item.Legend 208 may be configured to dynamically update with informationcorresponding to the zoom level of image 204.

Similarly, FIGS. 25-26 show representative cultural factor dataassociated with linguistics isolation, which is defined in thisembodiment as referring to the prevalence of families and/or theproportion of the population in the selected geographic location thathave no one over the age of 14 having English as the primary language.FIGS. 27-28 show representative cultural factor data associated withspeaking primarily a foreign language, which is defined in thisembodiment as referring to the identities and prevalence of the primaryor preferred foreign languages spoken within the selected geographiclocation. Each of these cultural factor options for a selectedgeographic location may be displayed in the same way as discussed above.

FIGS. 29-30 show representative educational factor data associated withthe proportion of people having a selected level of education in aselected geographic location. For example, a user using system 110 mayidentify zip codes having a higher proportion of people that havecompleted only primary education, along with other socioeconomicstatistics about the population.

FIGS. 31-32 show representative economic factor data associated with theper capita income of people in a selected geographic location. FIGS.33-34 show another example of economic factor data reflecting thedistribution of income in the selected geographic location. System 110may use a zip code Gini coefficient, which is a measure of inequality ofa distribution (in this example, wealth) defined as a ratio with valuesbetween 0 and 1. The numerator is the area between the Lorenz curve ofthe distribution and the uniform distribution line. The denominator isthe area under the uniform distribution line. System 110 may display apop-up window representing an income distribution layer, which maycontains additional detailed information for the categoricaldistribution of income-to-poverty ratio. In one embodiment, theincome-to-poverty ratio is a family's or person's income divided bytheir poverty threshold, as defined by the US Census Bureau. Theincome-to-poverty ratio categories shown in FIG. 34 represent variationsof the poverty level within a zip code or geographic location. Ratiosbelow 1.00 (below 100% of poverty) are below the official povertydefinition provided by the US Census Bureau, while ratios of 1.00 orgreater (100% of poverty or greater) indicate income above the povertylevel. Ratios below 0.50 (50% of poverty) may be described as “severepoverty”, while those with ratios at/or above 1.00 but less than 1.25may be described as “near poverty”.

FIGS. 35-36 show representative economic factor data associated with therate of unemployment in a selected geographic location. FIGS. 37-38 showrepresentative economic factor data associated with the prevalenceand/or proportion of people not in the labor force in a selectedgeographic location. FIGS. 39-40 show representative economic factordata associated with the prevalence of families living in poverty in aselected geographic location. In one embodiment, poverty is defined bythe US Census Bureau as money income, before taxes, relative to familysize and composition and do not vary geographically. FIGS. 41-42 showrepresentative economic factor data associated with the prevalenceand/or proportion of disabled people who are living in poverty in aselected geographic location. This layer may identify the relationshipbetween disability and poverty and the impact of the foregoing onhealth.

FIGS. 43-44 show representative social factor data associated with theprevalence and/or proportion of people of a specific marital status,such as divorced, separated, widowed, and married, in a selectedgeographic location. FIGS. 45-46 show representative social factor dataassociated with the prevalence and/or proportion of families having afemale as the householder in a selected geographic location. In oneembodiment, a family household contains at least 2 persons—thehouseholder and at least one other person related to the householder bybirth, marriage, or adoption. FIG. 46 shows representative detailedsocial factor data for female as the householder together with thedistribution by race/ethnic groups. FIGS. 47-48 show representativesocial factor data associated with the prevalence and/or proportion ofpeople without access to a vehicle in a selected geographic location.FIGS. 49-50 show representative economic factor data associated with theproportion of the population enrolled in Supplemental NutritionalAssistance Program (SNAP) in a selected geographic location. FIGS. 51-52show representative social factor data associated with the prevalenceand/or proportion of families exceeding the average family size in aselected geographic location.

To display one or more of the images described above in graphical userinterface (GUI) 101, system 110 may be configured as one or more layerspositioned on top of the reference map powered by the external server(e.g., Google®). Any of the community mapping factors or socialdeterminants of health factors described above may be combined with oneanother to express or filter the data in any one of a number of ways.The resulting image tiles, raster files, and/or shapefiles may bestored/saved for future recall to avoid having to retrace one's steps toarrive at the same window sizing and selection of factors and location.Any of the resulting images may be captured, bookmarked, and ortransmitted to another user via email, chat, or any other connectivitytool.

One or more aspects of server system 110 are operable by one or morecomputers and/or one or more programmable logic controllers (PLC's). Thecomputers and/or PLC's may be connected to one another and to othercomputers or devices via a wired or wireless network. These devices maybe connected to one or more remote computers and/or web servers via awired or wireless connection to the Internet.

The computers and one or more PLC's include a processor, such as acentral processing unit (CPU), for executing software, particularlysoftware stored in memory or on any computer readable medium, for use byor in connection with any computer related system or method.

A computer readable medium includes any electronic, magnetic, optical,or other physical device or apparatus that can contain or store acomputer program for use by or in connection with a computer relatedsystem or method. Memory can include any one or a combination ofvolatile memory elements (e.g., random access memory (RAM, such as DRAM,SRAM, SDRAM, etc.)) and nonvolatile memory elements (e.g., ROM, harddrive, tape, CDROM, etc.). Moreover, memory may incorporate electronic,magnetic, optical, and/or other types of storage media. Memory can havea distributed architecture where various components are situated remotefrom one another, but are still accessed by a processor.

The software may include one or more separate programs comprisingordered listings of executable instructions for implementing logicalfunctions. The software stored in memory or on any computer readablemedium may include one or more computer programs, each includingexecutable instructions executed by the processor. An operating systemmay control the execution of other computer programs and can providescheduling, input-output control, file and data management, memorymanagement, and communication control and related services.

In one embodiment, the PLC may include a computer processor such as acentral processing unit (CPU), memory, operating software stored inmemory, and various input and output (I/O) devices or data paths. TheI/O devices may include input devices, such as a keyboard, mouse, touchscreen, and/or any other user interface. The I/O devices may alsoinclude output devices, such as a computer display, a modem, a router,serial and parallel wired and wireless communication components and anyother elements needed to connect to, for example, another computer ordevice via a local network or the Internet whether wired or wirelessly.

While specific embodiments have been described in detail, it will beappreciated by those skilled in the art that various modifications andalternatives to those details could be developed in light of the overallteachings of the disclosure. Accordingly, the disclosure herein is meantto be illustrative only and not limiting as to its scope and should begiven the full breadth of the appended claims and any equivalentsthereof.

What is claimed is:
 1. A geographic population health informationsystem, comprising: (i) one or more first servers configured to: receivea request from a client system for a geographical area and a desiredsegmenting of the geographical area; command a geo-spatial database todeliver one or more shapefiles based on the geographical area and thedesired segmenting of the geographical area, the one or more shapefilesincluding polygons with vertices having coordinates defining staticgeographic boundaries of zip codes within the geographical area; servethe shapefiles to the client system; (ii) the client system configuredto: receive health data after receiving the served shapefiles, eachportion of the received health data including a respective geolocation;match at least some of the zip codes of the served shapefiles todifferent portions of the received health data based on the respectivegeolocations; generate shading instructions for at least some of thegeographic boundaries of the matched zip codes based on the portions ofthe health data that match with the matched zip codes; produce aplurality of image tiles based on the geographic boundaries of theserved shapefiles and the shading instructions of the matched zip codes;arrange and display the plurality of image tiles on a graphical userinterface of the client system.
 2. The system of claim 1, wherein thegeographical area of the request comprises coordinates of a center ofthe geographical area and a zoom level.
 3. The system of claim 2,wherein the one or more servers are configured to command thegeo-spatial database to deliver the one or more shapefiles for thegeographic boundaries based on the center of the geographical area andthe zoom level.
 4. The system of claim 3, wherein the zoom levelcorresponds to a current zoom level of the graphical user interface ofthe client system.
 5. The system of claim 1, further comprising one ormore second servers, the one or more second servers storing hypertensionprevalence data for each of the zip codes.
 6. The system of claim 5,wherein the client system is configured to receive the hypertensionprevalence data as the health data and generate the shading instructionsfor the matched zip codes based on the received hypertension prevalencedata.
 7. The system of claim 5, wherein the one or more second serversare configured to serve at least some of the health data to the clientsystem in a tabular format.
 8. The system of 7, wherein the clientsystem is configured to display the at least some of the health data inthe tabular format in response to a user selection.
 9. The system ofclaim 1, wherein the client system is configured to map a user selectionof a pixel of at least one of the one or more image tiles to the portionof the received health data matched with a polygon encompassing thepixel.
 10. The system of claim 9, wherein the client system isconfigured to display the matched portion of the received health data intabular form in response to the user selection of the pixel.
 11. Thesystem of claim 1, wherein at least one of the polygons defining thegeographic boundaries is irregular.
 12. A geographic population healthinformation system, comprising: one or more first servers configured to:receive a request from a client system for a layer including (a) healthdata (b) a geographical area, and (c) a desired segmenting granularityof the geographical area; command a geo-spatial database to deliver oneor more shapefiles based on the geographical area and the desiredsegmenting granularity of the geographical area, the one or moreshapefiles including polygons with vertices having coordinates definingstatic geographic boundaries of the desired segmenting granularity ofthe geographical area; receive the health data from one or more secondservers, each portion of the received health data including a respectivegeolocation; match at least some of the static geographic boundarieswith the desired segmenting granularity to different portions of thereceived health data based on the respective geolocations; generateshading instructions for at least some of the matched geographicboundaries based on the portions of the health data that match with thematched geographic boundaries; produce a plurality of image tiles basedon the matched geographic boundaries of the shapefiles and the shadinginstructions for the matched geographic boundaries; serve the pluralityof image tiles to the client system.
 13. The system of claim 12, whereinthe geographical area of the request comprises coordinates of a centerof the geographical area and a zoom level.
 14. The system of claim 13,wherein the one or more servers are configured to command thegeo-spatial database to deliver the one or more shapefiles for thegeographic boundaries based on the center of the geographical area andthe zoom level.
 15. The system of claim 13, wherein the zoom levelcorresponds to a current zoom level of a graphical user interface of theclient system.
 16. The system of claim 12, further comprising the one ormore second servers configured for storing hypertension prevalence datafor each of a plurality of zip codes.
 17. The system of claim 16,wherein the one or more first servers are configured to receive thehypertension prevalence data as the health data and generate the shadinginstructions for the matched geographic boundaries based on the receivedhypertension prevalence data.
 18. The system of claim 16, wherein theone or more first servers are configured to serve at least some of thehealth data to the client system in a tabular format.
 19. The system of17, further comprising the client system configured to display the atleast some of the health data in the tabular format in response to auser selection.
 20. The system of claim 12, further comprising theclient system configured to assemble and arrange the plurality of imagetiles received from the one or more first servers in an array of imagetiles.
 21. The system of claim 20, wherein the one or more first serversare configured to serve tile arrangement instructions to the clientsystem along with the plurality of image tiles and the client system isconfigured to arrange the plurality of image tiles into the array basedon the tile arrangement instructions.
 22. The system of claim 12,wherein in response to the request, the one or more first servers areconfigured to dynamically match each portion of the health data with thegeographic boundaries of the desired segmenting granularity, generatethe shading instructions, produce the plurality of image tiles, andserve the plurality of image tiles.
 23. The system of claim 12, wherein,to receive the desired segmenting granularity of the geographical area,the one or more first servers are configured to receive a user selectionfrom a plurality of granularity levels for a graphical user interface.24. The system of claim 23, wherein the list of granularity levelsincludes a city boundary, a zip code, and a state line.